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This study aims to describe the planning, implementation, and assessment of differentiated instruction in teaching descriptive text writing to ninth-grade students at SMP Negeri 2 Bendo, Magetan Regency. The study was conducted in response to students difficulties in generating ideas, selecting appropriate vocabulary, organizing ideas coherently, and producing vivid descriptive texts. This research employed a qualitative approach with a case study design. Data were collected through lesson plan observation, classroom observation, teacher interviews, and documentation of student learning products. The findings indicate that differentiated instruction was planned through a Merdeka Curriculum-based teaching module, diagnostic assessment, contextual material selection, and the use of PowerPoint, observation sheets, and tiered student worksheets. The implementation emphasized process and learning-environment differentiation through triggering questions, direct observation of real objects around the school, group work, individual scaffolding, immediate feedback, and reflection. Assessment was carried out continuously through diagnostic, formative, and summative assessment. Differentiated instruction helped students generate concrete ideas, organize their writing more systematically, increase motivation, and strengthen descriptive text writing skills. These findings affirm that differentiated instruction can serve as an adaptive strategy in Indonesian language learning at junior high school level.

The implementation of web-based archive digitalization can help improve performance in the field of archive recording, which was previously still manual at the Naval Academy. Some of the obstacles include archiving that is still manual, many files lost due to piled-up storage systems, and human resources in the field of archiving that are still lacking. This study aims to increase time and cost efficiency in archive processing, reduce the risk of loss and damage to archives, and improve the abilities and skills of human resources in the process of using digital archives. This type of research is descriptive qualitative. The data collection techniques are interviews, observation, and documentation with respondents as well as appropriate documentation. The data analysis was carried out through the processes of data reduction, data display, as well as verification or drawing conclusions. The research results can help improve the efficiency and security of archiving by minimizing risks, so that archive management can enhance efficiency and effectiveness, focusing on the implementation of web-based applications.


Hypertension is one of the leading non-communicable diseases contributing significantly to cardiovascular morbidity and mortality worldwide. Despite the availability of extensive electronic medical record data in healthcare institutions, these data are often utilized only for administrative reporting rather than predictive analysis. Consequently, opportunities to identify age groups with a higher probability of developing hypertension remain underutilized. This study aims to implement the Naïve Bayes classification algorithm to analyze age distribution and classify the risk of hypertension among patients using healthcare data. The research adopted the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, including business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Patient medical record data consisting of demographic and clinical attributes, including age, systolic blood pressure, diastolic blood pressure, body weight, gender, and hypertension status, were processed using the Naïve Bayes algorithm. Model performance was evaluated using a confusion matrix by measuring accuracy, precision, recall, specificity, and balanced accuracy. The implementation demonstrates that the Naïve Bayes algorithm is capable of classifying hypertension risk efficiently while providing probabilistic information regarding age groups with a higher tendency to experience hypertension. The resulting classification model offers an effective decision-support tool for healthcare providers in conducting targeted screening, preventive interventions, and evidence-based health planning. The findings also indicate that data mining techniques can transform routinely collected medical records into valuable clinical knowledge for early hypertension prevention and healthcare decision-making.

Manual teaching journal management at SMA Negeri 1 Kayen frequently leads to documentation inefficiencies, risks of data loss, and challenges in the teaching supervision process. This research tends to design and develop a web-based teacher teaching journal information system employing the CodeIgniter 3 framework with a Model-View-Controller (MVC) architecture. The system was improved employing the Waterfall methodology, comprising requirements analysis, system design, implementation, testing, and maintenance phases. The system integrates four user roles—administrator, teacher, student, and supervisor—to support the digitalization of recording processes, real-time teacher attendance verification by students, and centralized activity monitoring. Black Box Testing outcomes present that all system functions, involving authentication, data management, and reporting, operate 100% in accordance with user requirements. The implementation of this system effectively reduces administrative time compared to manual methods while enhancing the accountability and transparency of teaching journal management within the school. With centralized data integration, this system helps as an effective solution for supporting data-driven managerial decision-making in education.

This research was conducted at the Semarang City Public Works Department, particularly in the secretariat section responsible for correspondence administration and public information management (PPID). The study focuses on the conventional management of letter disposition, which makes it difficult for PPID officers to monitor letter status quickly, reduces process transparency, and may cause delays in decision-making and public services. This research aims to develop and implement a Disposition Monitoring Information System (SIMODIS) to digitize correspondence administration so that it becomes more effective, efficient, transparent, and accountable. The study uses ASTRID Analysis to identify strategic issues and a Design Thinking approach consisting of the Empathize, Define, Ideate, and Prototype stages. Empathy Map and Persona were also used to understand user needs. System testing was conducted using Black Box Testing to assess functionality and the System Usability Scale (SUS) to evaluate user experience. The results show that SIMODIS was successfully developed with features such as an admin dashboard, digital disposition forms, and a public mail status search portal. The SUS score reached 83, categorized as Excellent, indicating high usability and user acceptance.

Evaluating food portions and types in the Free Nutritious Meal (MBG) program is generally still performed manually, which is time-consuming and potentially subjective. This study aims to develop an automated deep learning-based system to efficiently detect food types and estimate their nutritional value. The method used is a quantitative experiment integrating the YOLOv11m architecture for real-time object detection and the Google Gemini 2.5 Flash Large Language Model (LLM) for contextual nutritional estimation reasoning. The model training utilized a dataset of 2,630 food tray images categorized into five classes (fruit, side dish, staple food, vegetable, milk) that had undergone an augmentation process. The results showed that the YOLOv11m model achieved excellent performance with a mean Average Precision (mAP@0.5) of 0.9727 and the highest F1-score of 0.9522 at a confidence threshold of 0.1. Furthermore, validation of the LLM integration demonstrated a high prediction agreement rate of 85%. In conclusion, the combination of the YOLOv11m algorithm and LLM reasoning is capable of detecting and validating nutritional classification quickly and precisely, showing strong potential as an objective nutritional evaluation monitoring solution for large-scale MBG program implementation.

This community service program aims to enhance farmers’ literacy on independent fertilizer production and strengthen their understanding of farmers’ rights within national fertilizer governance as an effort to achieve food sovereignty. The program was implemented in Belang Village, Bungkal Sub-district, Ponorogo Regency, involving GAPOKTAN Baungan consisting of farmer groups from Tempel, Kepuh, Pakal, Kanigoro, and Klatakan hamlets. This initiative represents cross-university synergy involving lecturers from Universitas Merdeka Malang, Universitas Soerjo Ngawi, Universitas Muhammadiyah Ponorogo, and Akademi Kesejahteraan Sosial Ibu Kartini Semarang. The implementation adopted a participatory hybrid approach combining Zoom Meeting dissemination and offline field activities. Activities included literacy enhancement on independent fertilizer production, training on organic fertilizer processing, strengthening farmer group institutions, and legal literacy regarding farmers’ rights in accessing subsidized fertilizers, including RDKK mechanisms and national policies. Methods comprised participatory socialization, hands-on training, group discussions, field practice, and monitoring and evaluation. Results show improved understanding of independent fertilizer concepts, increased technical skills in organic fertilizer production, and greater awareness of farmers’ rights and obligations in the fertilizer distribution system. The program strengthened inter-university collaboration and farmer networks, supporting sustainability, farmer independence, reduced dependence on chemical fertilizers, and community-based food sovereignty.

This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management

This study aims to implement the Cooperative Integrated Reading and Composition (CIRC) learning model to improve collaboration skills and learning outcomes among phase E students in class X-3 at SMA Katolik 2 Kabanjahe in Catholic Religious Education. This research employed Classroom Action Research conducted in two cycles, consisting of planning, implementation, observation, and reflection stages. Data were collected through observation sheets, learning outcome tests, and documentation, then analyzed using descriptive qualitative analysis supported by process and learning achievement indicators. The findings showed that the implementation of the CIRC learning model improved across learning stages, including orientation from 87% to 95%, organization from 90% to 97%, concept introduction from 87% to 92%, publication from 93% to 98%, and reflection and reinforcement from 87% to 98%. Students’ collaboration skills also increased in each indicator, namely working productively from 75% to 88%, actively participating in problem solving from 82% to 88%, maintaining a balance between listening and speaking from 76% to 86%, appreciating group members’ contributions from 73% to 87%, and demonstrating responsibility as group members from 77% to 93%. Learning outcomes also improved, as shown by the increase in the proficient category from 27% to 77%, while the basic and developing categories decreased to 0% in cycle II. These results indicate that CIRC effectively enhances students’ active participation, collaboration, responsibility, and learning achievement. Therefore, CIRC is recommended as an alternative collaborative learning model for Catholic Religious Education, particularly in strengthening cooperative interaction and meaningful understanding of religious learning materials in classroom practice.

Agrarian conflict remains one of the most persistent issues in Indonesia, particularly involving indigenous communities, government institutions, and private corporations. This study aims to analyze the dynamics of agrarian conflict, the role of agenda control in policymaking, and the effectiveness of conflict resolution between the Soge Natarmage and Goban Runut-Tana Ai Indigenous Communities and PT Kristus Raja Maumere (Krisrama) in Nangahale Village, Sikka Regency. This research employed a qualitative approach using a case study method. Data were collected through in-depth interviews, observation, and document analysis, and were analyzed using the interactive model of Miles, Huberman, and Saldaña. The findings reveal that the conflict is rooted in competing claims between the company's formal Land Cultivation Rights (Hak Guna Usaha/HGU) and the indigenous communities’ historical claims over customary land. The conflict resolution process has been largely dominated by a legal-formal approach that prioritizes HGU legality, while the recognition of indigenous land rights has received limited attention. The study further identifies the presence of agenda control and nondecision making practices that influence the direction of conflict resolution policies. Moreover, mediation efforts have not adequately addressed the root causes of the conflict because they remain focused on administrative and legal aspects rather than the social, cultural, and historical dimensions of indigenous communities. The study concludes that sustainable agrarian conflict resolution requires a more inclusive, participatory, and equitable approach through the recognition of indigenous rights and the involvement of all stakeholders in policymaking processes.

The regulation of the 14-day time limit for investigating regional head election crimes, as stipulated in Article 146 of Law Number 10 of 2016 concerning the election of governors, regents, and mayors, was established to accelerate law enforcement, ensure legal certainty, and maintain the relevance of election crime resolution within the strict and sequential stages of elections. However, in practice, this provision often creates legal problems when investigations must be terminated due to the expiration of the time limit, even though strong indications of election crimes exist. This situation raises a legal issue because law enforcement, although procedurally compliant, does not fully achieve substantive justice and legal utility, particularly in maintaining public trust, legal order, and democratic integrity. This study aims to analyze the theoretical basis of the 14-day investigation limit and examine the application of justice and legal utility principles in terminating election crime investigations due to time expiration. The research uses a normative legal method with statutory, conceptual, and analytical approaches. The findings indicate that the 14-day limit is grounded in the principle of lex specialis, legal certainty, speedy trial principles, electoral justice theory, and the effectiveness of integrated law enforcement. This limitation is intended to prevent prolonged legal processes, protect the legal status of reported parties, ensure smooth election stages, and maintain regional democratic stability.

Flooding remains a recurrent hazard in the Special Capital Region of Jakarta (DKI Jakarta), causing substantial disruptions across multiple dimensions community life, including social well-being and economic activities. The availability of flood-related information through the Jakarta One Data Portal (Satu Data Jakarta) provides significant opportunities for broader data utilization; however, transforming such information into meaningful assessments regional vulnerability requires a systematic analytical approach to generate more comprehensive understanding of the conditions of individual urban villages (kelurahan). This study focuses on the classification areas based on the characteristics and impacts of flood events occurring throughout DKI Jakarta. The analysis utilizes flood event records from 2023 to 2025 and incorporates several indicators, including the number of flood occurrences, the number of affected neighborhood associations (RW), the number affected households, the number of affected residents, the number of evacuees, the number of evacuation sites, and floodwater depth. Data processing was conducted using the Knowledge Discovery in Databases (KDD) framework, encompassing data selection, cleaning and preprocessing, transformation, pattern exploration, result evaluation, and knowledge extraction. The findings demonstrate that three-cluster solution effectively captures variations in flood vulnerability levels, corresponding to low-, moderate-, and high-risk categories. A total of 96 urban villages were classified as low-risk, 27 as moderate-risk, and 46 as high-risk areas. The resulting clustering patterns provide a clearer spatial representation of flood-risk distribution across urban villages, thereby offering valuable insights for the development more targeted mitigation strategies, the prioritization of flood management interventions, and the enhancement of evidence-based decision-making processes in DKI Jakarta.

Aromatherapy is the use of essential oils derived from natural materials to improve physical and psychological well-being. One of the most popular aromatherapy products is the aromatherapy candle, which provides relaxation while creating a comfortable atmosphere. This study aimed to develop aromatherapy candles based on agarwood (Aquilaria malaccensis) leaf extract, evaluate product quality, analyze public acceptance, and identify their potential as an entrepreneurial opportunity. This study employed an experimental method with a descriptive approach. The research stages included the extraction of agarwood leaves through a distillation process, the formulation of aromatherapy candles, product validation by three experts using sensory evaluation, and a public acceptance test involving 40 respondents using a Likert-scale questionnaire. The results showed that the third experiment produced the best extract characteristics, including a golden-yellow color, a stronger distinctive agarwood aroma, and an oily texture. The public acceptance test indicated that the average scores for color, texture, ease of use, and aroma were 3.16, 2.90, 3.42, and 3.02, respectively, which were categorized as good to very good. These findings demonstrate that agarwood leaf extract has the potential to be used as an alternative ingredient in the production of aromatherapy candles, in addition to receiving a high level of public acceptance, the product possesses economic value and can be developed as an innovative product and entrepreneurial opportunity in the beauty, spa, wellness, and creative industries.

One of the most significant foods for the people of Indonesia, tempeh is made mostly from soybeans. Soybean quality selection is still mostly done by hand, relying on eye inspection and the expertise of business actors. This may cause subjective evaluations, lengthy decision-making processes, and uneven outcomes. With the TOPSIS technique as its foundation, this project intends to construct a Decision Support System (DSS) for selecting high-quality soybeans. Color, texture, price, scent, and flavor are some of the evaluation criteria. Observations and interviews were conducted in Rumah Tempe A-Zaki Padang to gather data for the research. Ranking the options according to how close they were to the positive ideal solution and how far away from the negative ideal solution was done using the TOPSIS approach. In terms of preference values, the Green Soybean option came out on top with 0.9692, followed by Black Soybeans with 0.2335, Yellow Soybeans with 0.1516, and Brown Soybeans with 0.1181. Based on these outcomes, it seems that TOPSIS can indeed provide objective suggestions for soybean selection according to a number of different standards. Business players in the tempeh industry may benefit from this decision support system by using it to choose high-quality soybean raw materials more efficiently and accurately.

The benefit of cardboard waste as a headpiece is to encourage the entrepreneurial spirit to continue to be creative in processing this inorganic waste into products at prices that are relatively cheap compared to prices on the market. Data collection uses the methods of Observation, Literature, Experimentation, Documentation, Interviews, Questionnaires. The author carried out the process of using cardboard waste to make headpieces through several stages, not only that, the author also carried out experiments 3 times using different dyes. In experiment 1 using gold pilok, experiment 2 used gold pilok then sprinkled with gold glitter, then experiment 3 used wall paint coloring sprinkled with gold glitter. The author conducted a sensory test regarding the public's acceptance of headpiece products made from cardboard waste. The highest average results were obtained in experiment 3 with a total average color of 2.87 which means quite appropriate, a total average texture of 2.63 which means quite suitable, a total average design of 1.77 which is less appropriate, while the total average ease of use is 2.67, which means it is quite appropriate. So the results obtained were that as many as 30 respondents preferred product 3 with quite appropriate criteria. From the results of the products made, the coloring still needs to be improved so that they are more perfect and the designs are developed to be more varied so that they can be used as a reference for further research.

Embroidery is one of Indonesia’s traditional craft arts that has developed over time and continues to attract people from various social backgrounds. Embroidery techniques are commonly applied to fashion products as well as household items. The diversity of embroidery motifs and techniques provides aesthetic value and uniqueness to each product, making embroidery an important element in the development of the fashion industry. This opportunity can encourage students of the Fashion Design Program at AKS Ibu Kartini to develop their entrepreneurial potential through creativity in manual embroidery. This study employed a quantitative approach using multiple linear regression analysis as the data processing technique to determine the influence of internal factors on the entrepreneurial motivation of Fashion Design students at AKS Ibu Kartini. The research sample consisted of 65 respondents. The findings revealed that, simultaneously, the four independent variables had a significant effect on entrepreneurial motivation, with a coefficient of determination (R²) value of 0.910. This indicates that 91% of the variation in entrepreneurial motivation can be explained by technical knowledge (X1), technical skills (X2), creativity and innovation (X3), and entrepreneurial mindset (X4), while the remaining 9% is influenced by other factors outside this study. Partially, variables X1, X2, and X4 showed a positive and significant effect on entrepreneurial motivation, whereas X3 demonstrated a negative and significant effect. This finding indicates that creativity without market orientation may reduce students’ motivation to engage in entrepreneurship. The implications of this study emphasize the importance of improving students’ knowledge, skills, and entrepreneurial mindset. Furthermore, proper guidance is needed to ensure that students’ creativity and innovation are aligned with market demands in order to optimally enhance entrepreneurial motivation.

Classroom management is an important aspect of creating a conducive learning environment and supporting the achievement of learning objectives. This study aims to analyze the permissive approach and the cookbook approach in classroom management based on the results of an interview with a teacher. The research employed a descriptive qualitative method, with interviews used as the primary data collection technique. The findings indicate that the teacher does not fully implement either the permissive approach or the cookbook approach. The teacher provides students with freedom within limits that support the learning process while still enforcing agreed-upon classroom rules. In addition, the teacher does not rely on rigid procedures but instead adapts classroom management strategies to students' characteristics and the situations encountered in the classroom. The study reveals that the teacher tends to adopt an adaptive classroom management approach by combining firmness, empathy, and flexibility, thereby creating an orderly, comfortable, and effective learning environment that supports the achievement of educational objectives.

Stroke is a neurological disorder caused by impaired blood flow to the brain, resulting in brain tissue damage and various functional impairments. One of the common problems experienced by stroke patients is sleep disturbance, which may be influenced by neurological deficits, limited physical mobility, pain, and post-stroke anxiety. Persistent sleep disturbances can delay the recovery process and reduce patients’ quality of life. The long-term use of sleeping medications may lead to adverse effects; therefore, safe and easily applicable complementary therapies are needed. This study aimed to determine the effectiveness of peppermint oil aromatherapy in improving sleep quality among stroke patients in the working area of Barebbo Community Health Center, Bone Regency. The method used was the implementation of complementary therapy through the administration of peppermint oil aromatherapy to stroke patients experiencing sleep disturbances. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) before and after the intervention. The assessment results showed that before the intervention, patients experienced poor sleep quality, characterized by difficulty initiating sleep, frequent nighttime awakenings, insufficient sleep duration, and daytime fatigue. After receiving peppermint oil aromatherapy, patients demonstrated increased comfort, reduced anxiety, improved ability to initiate sleep, and better overall sleep quality compared to their condition before the intervention. Therefore, peppermint oil aromatherapy was found to be effective in improving sleep quality among stroke patients and can be used as a complementary non-pharmacological intervention in nursing care.

In the post-pandemic period, the learning process at the Madrasah Tsanawiyah level continues to face significant challenges, particularly the emergence of disparities in student learning outcomes in general subjects. Many students have not yet fully returned to an active and focused learning pattern, resulting in uneven learning outcomes. Under these circumstances, self-directed learning has become an increasingly prominent aspect, as it relates to students’ ability to manage their own learning process without relying too heavily on teacher guidance. This study aims to examine how learning autonomy influences MTs students’ learning outcomes by reviewing existing studies. The research employs a literature review method using a qualitative descriptive approach, drawing on scientific sources from the past five years. The data were analyzed through content analysis to identify patterns of relationships emerging from previous studies. The results of the study indicate that learning autonomy tends to have a positive correlation with improved learning outcomes, although the magnitude of the effect is not always consistent across every study. Students who are better able to manage their own learning steps generally appear more active, more focused in their studies, and more aware of the processes they are undergoing. Nevertheless, the development of learning autonomy does not occur in isolation, as it remains influenced by the school’s learning environment and the way teachers manage instruction. Thus, it is clear that fostering independent learning is a key factor in efforts to improve student learning outcomes in the post-pandemic era.

This qualitative literature review examines how global litigation finance markets manage the tension between transparency requirements and innovation dynamics. Drawing on academic scholarship, policy reports, court decisions, and industry analyses, the review synthesizes evidence on disclosure obligations, funder influence, national security concerns, and emerging regulatory models. Findings show that while transparency enhances judicial integrity and mitigates conflicts of interest, excessive disclosure may undermine commercial confidentiality and inhibit investment in complex claims. Across jurisdictions, regulatory debates converge on the need for proportionate, court directed mechanisms such as limited in camera disclosure, provenance checks, and funder conduct safeguards. The review concludes that transparency and innovation are not mutually exclusive; instead, balanced regulatory frameworks can preserve market efficiency while protecting due process values and preventing geopolitical misuse. The study highlights significant data gaps and calls for deeper empirical research to guide evidence based policy making.